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Peripheral nerve function estimation by linear model of multi‐CMAP responses for surgical intervention in acoustic neuroma surgery

Nerve function assessments are crucial for surgical intervention during acoustic neuroma surgery. Cranial nerves such as acoustic and facial nerves, can be possibly damaged during tumor dissection. Proper surgical intervention should prevent neurological deficit and achieve total tumor removal. Conv...

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Autores principales: Puanhvuan, Dilok, Chumnanvej, Sorayouth, Wongsawat, Yodchanan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5727268/
https://www.ncbi.nlm.nih.gov/pubmed/29192065
http://dx.doi.org/10.14814/phy2.13495
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author Puanhvuan, Dilok
Chumnanvej, Sorayouth
Wongsawat, Yodchanan
author_facet Puanhvuan, Dilok
Chumnanvej, Sorayouth
Wongsawat, Yodchanan
author_sort Puanhvuan, Dilok
collection PubMed
description Nerve function assessments are crucial for surgical intervention during acoustic neuroma surgery. Cranial nerves such as acoustic and facial nerves, can be possibly damaged during tumor dissection. Proper surgical intervention should prevent neurological deficit and achieve total tumor removal. Conventionally, nerve function is qualitatively evaluated by surgeon and neurologist. Facial nerves can be preserved by monitoring the compound muscle action potential (CMAP) response. The differences in the amplitude and latency of CMAP are used as indicators during surgical interventions. However, baseline CMAPs cannot be recorded in the presence of large acoustic tumors. This paper presents a new way of estimating nerve function. Instead of a single CMAP examination, multi‐CMAP responses are obtained from a train of varied stimulus intensities and these are applied a mathematical model. Shifts in the mathematical model parameters reflect changes in facial nerve function. In this study, experiments conducted in frog revealed that shifts in the linear model parameters were related to the level of induced nerve injury. Significant differences in the slope parameter of the linear model were found between each nerve condition. The identification of healthy and severed nerves via a support vector machine (SVM) corresponded to 94% accuracy. This classification criterion could be used with surgical intervention to prevent severed facial nerve palsy in acoustic neuroma surgery. The proposed method could be used to estimate nerve outcomes without prior information of a CMAP baseline.
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spelling pubmed-57272682017-12-13 Peripheral nerve function estimation by linear model of multi‐CMAP responses for surgical intervention in acoustic neuroma surgery Puanhvuan, Dilok Chumnanvej, Sorayouth Wongsawat, Yodchanan Physiol Rep Original Research Nerve function assessments are crucial for surgical intervention during acoustic neuroma surgery. Cranial nerves such as acoustic and facial nerves, can be possibly damaged during tumor dissection. Proper surgical intervention should prevent neurological deficit and achieve total tumor removal. Conventionally, nerve function is qualitatively evaluated by surgeon and neurologist. Facial nerves can be preserved by monitoring the compound muscle action potential (CMAP) response. The differences in the amplitude and latency of CMAP are used as indicators during surgical interventions. However, baseline CMAPs cannot be recorded in the presence of large acoustic tumors. This paper presents a new way of estimating nerve function. Instead of a single CMAP examination, multi‐CMAP responses are obtained from a train of varied stimulus intensities and these are applied a mathematical model. Shifts in the mathematical model parameters reflect changes in facial nerve function. In this study, experiments conducted in frog revealed that shifts in the linear model parameters were related to the level of induced nerve injury. Significant differences in the slope parameter of the linear model were found between each nerve condition. The identification of healthy and severed nerves via a support vector machine (SVM) corresponded to 94% accuracy. This classification criterion could be used with surgical intervention to prevent severed facial nerve palsy in acoustic neuroma surgery. The proposed method could be used to estimate nerve outcomes without prior information of a CMAP baseline. John Wiley and Sons Inc. 2017-11-30 /pmc/articles/PMC5727268/ /pubmed/29192065 http://dx.doi.org/10.14814/phy2.13495 Text en © 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Puanhvuan, Dilok
Chumnanvej, Sorayouth
Wongsawat, Yodchanan
Peripheral nerve function estimation by linear model of multi‐CMAP responses for surgical intervention in acoustic neuroma surgery
title Peripheral nerve function estimation by linear model of multi‐CMAP responses for surgical intervention in acoustic neuroma surgery
title_full Peripheral nerve function estimation by linear model of multi‐CMAP responses for surgical intervention in acoustic neuroma surgery
title_fullStr Peripheral nerve function estimation by linear model of multi‐CMAP responses for surgical intervention in acoustic neuroma surgery
title_full_unstemmed Peripheral nerve function estimation by linear model of multi‐CMAP responses for surgical intervention in acoustic neuroma surgery
title_short Peripheral nerve function estimation by linear model of multi‐CMAP responses for surgical intervention in acoustic neuroma surgery
title_sort peripheral nerve function estimation by linear model of multi‐cmap responses for surgical intervention in acoustic neuroma surgery
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5727268/
https://www.ncbi.nlm.nih.gov/pubmed/29192065
http://dx.doi.org/10.14814/phy2.13495
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